Study on the expression of TOP2A in hepatocellular carcinoma and its relationship with patient prognosis

Background Hepatocellular carcinoma (HCC) is a primary liver cancer with a high mortality rate. However, the molecular mechanism of HCC formation remains to be explored and studied. Objective To investigate the expression of TOP2A in hepatocellular carcinoma (HCC) and its prognosis. Methods The data set of hepatocellular carcinoma was downloaded from GEO database for differential gene analysis, and hub gene was identified by Cytoscape. GEPIA was used to verify the expression of HUB gene and evaluate its prognostic value. Then TOP2A was selected as the research object of this paper by combining literature and clinical sample results. Firstly, TIMER database was used to study TOP2A, and the differential expression of TOP2A gene between normal tissues and cancer tissues was analyzed, as well as the correlation between TOP2A gene expression and immune infiltration of HCC cells. Then, the expression of top2a-related antibodies was analyzed using the Human Protein Atlas database, and the differential expression of TOP2A was verified by immunohistochemistry. Then, SRTING database and Cytoscape were used to establish PPI network for TOP2A and protein–protein interaction analysis was performed. The Oncomine database and cBioPortal were used to express and identify TOP2A mutation-related analyses. The expression differences of TOP2A gene were identified by LinkedOmics, and the GO and KEGG pathways were analyzed in combination with related genes. Finally, Kaplan–Meier survival analysis was performed to analyze the clinical and prognosis of HCC patients. Results TOP2A may be a new biomarker and therapeutic target for hepatocellular carcinoma.

COL1A1 is a potential prognostic marker and therapeutic target in non-small cell lung cancer.

Background: Nowadays, non-small cell lung cancer (NSCLC) is a common and highly fatal malignancy in worldwide. Therefore, to identify the potential prognostic markers and therapeutic targets is urgent for patients. Objective: This study aims to find hub targets associated with NSCLC using multiple databases. Methods: Differentially expressed genes (DEGs) from Genome Expression Omnibus (GEO) cohorts were employed for the enrichment analyses of Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. Candidate key genes, filtered from the topological parameter 'Degree' and validated using the The Cancer Genome Atlas (TCGA) cohort, were analyzed for their association with clinicopathological features and prognosis of NSCLC. Meanwhile, immunohistochemical cohort analyses and biological verification were further evaluated. Results: A total of 146 DEGs were identified following data preprocessing, and a protein-protein interaction (PPI) systematic network was constructed based on them. The top ten candidate core genes were further extracted from the above PPI network by using 'Degree' value, among which COL1A1 was shown to associate with overall survival (OS) of NSCLC as determined by using the Kaplan-Meier analysis (p=0.028), and could serve as an independent prognostic factor for OS in NSCLC patients (HR, 0.814; 95% CI, 0.665-0.996; p=0.046). We then analyzed the clinical stages, PPI, mutations, potential biological functions and immune regulations of COL1A1 in NSCLC patients using multiple bioinformatics tools, including GEPIA, GeneMANIA, cBioPortal, GESA and TISIDB. Finally, we further experimentally validated the overexpression of COL1A1 in NSCLC samples, and found that inhibition of COL1A1 expression moderately sensitized NSCLC cells to cisplatin. Conclusion: Thus, our results show that COL1A1 may serve as a potential prognostic marker and therapeutic target in NSCLC.

Transcriptome and HPLC Analysis Reveal the Regulatory Mechanisms of Aurantio-Obtusin in Space Environment-Induced Senna obtusifolia Lines

Senna obtusifolia is a famous medicinal plant that is widely used in Asian countries. Its seed plays an important role in the treatment of many diseases because it contains various anthraquinones and flavonoids. Our previous studies have indicated that three space environment-induced S. obtusifolia lines (SP-lines) i.e., QC10, QC29, and QC46, have higher seed yield and aurantio-obtusin (AO) content. However, the underlying mechanism of higher AO content in SP-lines is still unknown. Herein, transcriptome sequencing and HPLC were employed to analyze the differences between SP-lines and ground control (GC3) and elucidate the regulatory mechanisms of AO accumulation in SP-lines. The results show that 4002 differentially expressed genes (DEGs) were identified in SP-lines versus (vs.) GC3. DEGs in the QC10 vs. GC3, QC29 vs. GC3, and QC46 vs. GC3 comparisons were classified into 28, 36, and 81 GO terms and involved in 63, 74, and 107 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG pathway and gene expression analysis revealed that DEGs involved in anthraquinone pathways were significantly elevated in QC10 and QC46. Integrating the results of GO annotation, KEGG enrichment, and gene expression analysis, we propose that the elevated genes such as DAHPS, DHQS, and MenB enhance the metabolic flux in the anthraquinone pathway and promote AO content in QC10 and QC46. Taken together, this study elucidated the mechanism of AO content in SP-lines and provides valuable genetic information for S. obtusifolia. In addition, to the best of our knowledge, this study presents the first transcriptome analysis of environment-induced medicinal plants and paves the way to select elite S. obtusifolia varieties in the future.

DNA Methylation Changes and Its Associated Genes in Mulberry (Morus alba L.) Yu-711 Response to Drought Stress Using MethylRAD Sequencing

Drought stress remains one of the most detrimental environmental cues affecting plant growth and survival. In this work, the DNA methylome changes in mulberry leaves under drought stress (EG) and control (CK) and their impact on gene regulation were investigated by MethylRAD sequencing. The results show 138,464 (37.37%) and 56,241 (28.81%) methylation at the CG and CWG sites (W = A or T), respectively, in the mulberry genome between drought stress and control. The distribution of the methylome was prevalent in the intergenic, exonic, intronic and downstream regions of the mulberry plant genome. In addition, we discovered 170 DMGs (129 in CG sites and 41 in CWG sites) and 581 DMS (413 in CG sites and 168 in CWG sites). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicates that phenylpropanoid biosynthesis, spliceosome, amino acid biosynthesis, carbon metabolism, RNA transport, plant hormone, signal transduction pathways, and quorum sensing play a crucial role in mulberry response to drought stress. Furthermore, the qRT-PCR analysis indicates that the selected 23 genes enriched in the KEGG pathways are differentially expressed, and 86.96% of the genes share downregulated methylation and 13.04% share upregulation methylation status, indicating the complex link between DNA methylation and gene regulation. This study serves as fundamentals in discovering the epigenomic status and the pathways that will significantly enhance mulberry breeding for adaptation to a wide range of environments.

Comprehensive exploration of the genetic contribution of the dopaminergic and serotonergic pathways to psychiatric disorders

Psychiatric disorders are highly prevalent and display considerable clinical and genetic overlap. Dopaminergic and serotonergic neurotransmission have been shown to play an important role in many psychiatric disorders. Here we aim to assess the genetic contribution of these systems to eight psychiatric disorders (attention-deficit hyperactivity disorder (ADHD), anorexia nervosa (ANO), autism spectrum disorder (ASD), bipolar disorder (BIP), major depression (MD), obsessive-compulsive disorder (OCD), schizophrenia (SCZ) and Tourette’s syndrome (TS)) using publicly available GWAS analyses performed by the Psychiatric Genomics Consortium that include more than 160,000 cases and 275,000 controls. To do so, we elaborated four different gene sets: two ‘wide’ selections for dopamine (DA) and for serotonin (SERT) using the Gene Ontology and KEGG pathways tools, and two’core’ selections for the same systems, manually curated. At the gene level, we found 67 genes from the DA and/or SERT gene sets significantly associated with one of the studied disorders, and 12 of them were associated with two different disorders. Gene-set analysis revealed significant associations for ADHD and ASD with the wide DA gene set, for BIP with the wide SERT gene set, and for MD with the core SERT set. Interestingly, interrogation of a cross-disorder GWAS meta-analysis of the eight psychiatric conditions displayed association with the wide DA gene set. To our knowledge, this is the first systematic examination of genes encoding proteins essential to the function of these two neurotransmitter systems in these disorders. Our results support a pleiotropic contribution of the dopaminergic and serotonergic systems in several psychiatric conditions.

Yogurt Enriched with Inulin Ameliorated Reproductive Functions and Regulated Gut Microbiota in Dehydroepiandrosterone-Induced Polycystic Ovary Syndrome Mice

The effects of synbiotic yogurt supplemented with inulin on the pathological manifestations and gut microbiota–bile acid axis were investigated using a dehydroepiandrosterone (DHEA)-induced polycystic ovary syndrome (PCOS) mice model. Female C57BL/6J mice were injected subcutaneously with DHEA at a dose of 6 mg/100 g BW for 20 days to establish a PCOS mouse model. Then, the PCOS mice were treated with yogurt containing inulin (6% w/w) at 15 mL/kg BW for 24 days. Results showed that supplementation of synbiotic yogurt enriched with inulin to PCOS mice decreased the body weight gain, improved estrus cycles and ovary morphology, and reduced the levels of luteinizing hormone while increasing the levels of follicle-stimulating hormone and interleukin-22 in serum. At the genus level, synbiotic yogurt increased the relative abundance of Lactobacillus, Bifidobacterium, and Akkermansia. PICRUSt analysis indicated that KEGG pathways including bile acid biosynthesis were changed after inulin-enriched synbiotic yogurt supplementation. Synbiotic yogurt enriched with inulin also modulated the bile acid profiles. In conclusion, inulin-enriched synbiotic yogurt alleviated reproductive dysfunction and modulated gut microbiota and bile acid profiles in PCOS mice.

Senecavirus A- and Non-Infected Cells at Early Stage of Infection: Comparative Metabolomic Profiles

Senecavirus A (SVA), classified into the genus Senecavirus in the family Picornaviridae, causes an infectious disease in pigs. This virus can efficiently replicate in some non-pig-derived cells, such as the BHK cell line and its derivative (BSR-T7/5 cell line). We had recovered a wild-type SVA from its cDNA clone previously, and then uncovered the proteomic profile of SVA-infected BSR-T7/5 cells at 12 h post inoculation (hpi). In order to explore the cellular metabolomics further, the SVA-inoculated BSR-T7/5 cell monolayer was collected at 12 hpi for assay via liquid chromatography-tandem mass spectrometry (LC-MS/MS). The resultant data set was comprehensively analyzed using bioinformatics tools. A total of 451 metabolites were identified using in-house and public databases. Out of these metabolites, sixty-one showed significantly differential values (p value < 0.05). The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to analyze metabolic pathways of the significantly differential metabolites. There were eighty-one identified KEGG pathways, out of which twenty-seven showed their p values < 0.05. The pyrimidine metabolism revealed the minimum p value and the maximum number of significantly differential metabolites, implying the pyrimidine played a key role in cellular metabolism after SVA infection. SVA replication must rely on the cellular metabolism. The present study on metabolomics would shed light on impacts of SVA-induced multiple interactions among metabolites on cells or even on natural hosts.

Machine learning-based predictions of dietary restriction associations across ageing-related genes

Background Dietary restriction (DR) is the most studied pro-longevity intervention; however, a complete understanding of its underlying mechanisms remains elusive, and new research directions may emerge from the identification of novel DR-related genes and DR-related genetic features. Results This work used a Machine Learning (ML) approach to classify ageing-related genes as DR-related or NotDR-related using 9 different types of predictive features: PathDIP pathways, two types of features based on KEGG pathways, two types of Protein–Protein Interactions (PPI) features, Gene Ontology (GO) terms, Genotype Tissue Expression (GTEx) expression features, GeneFriends co-expression features and protein sequence descriptors. Our findings suggested that features biased towards curated knowledge (i.e. GO terms and biological pathways), had the greatest predictive power, while unbiased features (mainly gene expression and co-expression data) have the least predictive power. Moreover, a combination of all the feature types diminished the predictive power compared to predictions based on curated knowledge. Feature importance analysis on the two most predictive classifiers mostly corroborated existing knowledge and supported recent findings linking DR to the Nuclear Factor Erythroid 2-Related Factor 2 (NRF2) signalling pathway and G protein-coupled receptors (GPCR). We then used the two strongest combinations of feature type and ML algorithm to predict DR-relatedness among ageing-related genes currently lacking DR-related annotations in the data, resulting in a set of promising candidate DR-related genes (GOT2, GOT1, TSC1, CTH, GCLM, IRS2 and SESN2) whose predicted DR-relatedness remain to be validated in future wet-lab experiments. Conclusions This work demonstrated the strong potential of ML-based techniques to identify DR-associated features as our findings are consistent with literature and recent discoveries. Although the inference of new DR-related mechanistic findings based solely on GO terms and biological pathways was limited due to their knowledge-driven nature, the predictive power of these two features types remained useful as it allowed inferring new promising candidate DR-related genes.

Integrated miRNA and mRNA Expression Profiles Reveal Differentially Expressed miR-222a as an Antiviral Factor Against Duck Hepatitis A Virus Type 1 Infection

Duck hepatitis A virus 1 (DHAV-1) is a highly contagious etiological agent that causes acute hepatitis in young ducklings. MicroRNAs (miRNAs) play important regulatory roles in response to pathogens. However, the interplay between DHAV-1 infection and miRNAs remains ambiguous. We characterized and compared miRNA and mRNA expression profiles in duck embryo fibroblasts cells (DEFs) infected with DHAV-1. In total, 36 and 96 differentially expressed (DE) miRNAs, and 4110 and 2595 DE mRNAs, were identified at 12 and 24 h after infection. In particular, 126 and 275 miRNA–mRNA pairs with a negative correlation were chosen to construct an interaction network. Subsequently, we identified the functional annotation of DE mRNAs and target genes of DE miRNAs enriched in diverse Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, which may be important for virus resistance, cell proliferation, and metabolism. Moreover, upregulated miR-222a could negatively regulate DHAV-1 replication in DEFs and downregulate integrin subunit beta 3 (ITGB3) expression by targeting the 3′ untranslated region (3′UTR), indicating that miR-222a may modulate DHAV-1 replication via interaction with ITGB3. In conclusion, the results reveal changes of mRNAs and miRNAs during DHAV-1 infection and suggest miR-222a as an antiviral factor against DHAV-1.

First high-quality genome assembly data of sago palm (Metroxylon sagu Rottboll)

The sago palm (Metroxylon sagu Rottboll) is a all-rounder palm, it is both a tropical halophytic starch-producing palm as well as an ornamental plant. Recently, a genome survey was conducted on this palm using Illumina sequencing platform but the BUSCO genome completeness is very low (21.5%) and most of them (~78%) are either fragmented or missing. Thus, in this study, the sago palm genome completeness was further improved with the utilization of the Nanopore sequencing platform that produced longer reads. A hybrid genome assembly was conducted and the outcome was a much complete sago palm genome with BUSCO completeness achieved at as high as 97.9% with only ~2% of them either fragmented or missing. The estimated genome size of the sago palm is 509,812,790 bp in this study. A sum of 33,242 protein-coding genes were revealed from the sago palm genome and around 96.39% of them had been functionally annotated. An investigation on the carbohydrate metabolism KEGG pathways also unearthed that starch synthesis was one of the major sago palm activities. These data are indispensable for future molecular evolutionary and genome-wide association studies.